An approach to multiattribute decision making with interval-valued intuitionistic fuzzy assessments and incomplete weights

7 This article proposes an approach to multiattribute decision making with incomplete 8 attribute weight information where individual assessments are provided as interval-valued 9 intuitionistic fuzzy numbers (IVIFNs). By employing a series of optimization models, the 10 proposed approach derives a linear program for determining attribute weights. The 11 weights are subsequently used to synthesize individual IVIFN assessments into an 12 aggregated IVIFN value for each alternative. In order to rank alternatives based on their 13 aggregated IVIFN values, a novel method is developed for comparing two IVIFNs by 14 introducing two new functions: the membership uncertainty index and the hesitation 15 uncertainty index. An illustrative investment decision problem is employed to 16 demonstrate how to apply the proposed procedure and comparative studies are conducted 17 to show its overall consistency with existing approaches. 18